ABSTRACT
In order to improve the emergency logistics support capacity of Wuhan city and build a transportation power pilot, based on the background of public health emergencies and on the basis of comprehensively summarizing the experience, practices and prominent problems of emergency logistics support work of COVID-19 in Wuhan City, this paper studies from the aspects of development foundation, overall thinking and main tasks, Put forward the systematic framework and specific implementation path of emergency logistics system construction of "building three guarantee systems of reserve facilities, transportation capacity and command and dispatching, and building an information platform”. At the same time, in the construction of emergency logistics command and coordination information platform, K-means clustering method is adopted to achieve scientific matching and efficient connection between emergency materials transit stations and demand points. For other cities It is of practical significance to improve the regional emergency logistics system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Technology and innovation have promoted industry convergence and brought new opportunities for industrial development, and a degree of convergence exists in the emergency logistics industry. The purpose of this study is to explore the convergence of the emergency logistics industry and the change in convergence degree among related industries, so as to find a solution to the lack of robustness of the emergency logistics system. This study measures the technical relationship between industries and analyzes the overall trend of emergency logistics industry convergence using the consistency between patent co-classification analysis and patent categories and technical fields. The dominance index and relative strength index are used to assess the strength of industry nodes and the convergence of the emergency logistics industry. Social network analysis is used to investigate the industries and technical fields that are important in the convergence industry. The findings indicate that there is significant convergence between the technical fields of the emergency logistics industry. Twelve industries are actively involved in the emergency logistics industry convergence, and nine industry pairs have strong convergence relationships between them. The information industry is critical to the convergence of the emergency logistics industry. Industry convergence is assisting in the coordinated growth of the emergency logistics sector, lowering informational barriers between sectors, and boosting the system's resilience. This study contributes theoretical significance to the development of the emergency logistics industry and enriches the emergency logistics industry's research system.
ABSTRACT
The novel coronavirus pandemic is a major global public health emergency, and has presented new challenges and requirements for the timely response and operational stability of emergency logistics that were required to address the major public health events outbreak in China. Based on the problems of insufficient timeliness and high total system cost of emergency logistics distribution in major epidemic situations, this paper takes the minimum vehicle distribution travel cost, time cost, early/late punishment cost, and fixed cost of the vehicle as the target, the soft time window for receiving goods at each demand point, the rated load of the vehicle, the volume, maximum travel of the vehicle in a single delivery as constraints, and an emergency logistics vehicle routing problem optimization model for major epidemics was constructed. The convergence speed improvement strategy, particle search improvement strategy, and elite retention improvement strategy were introduced to improve the particle swarm optimization (PSO) algorithm for it to be suitable for solving global optimization problems. The simulation results prove that the improved PSO algorithm required to solve the emergency medical supplies logistics vehicle routing problem for the major emergency can reach optimal results. Compared with the basic PSO algorithm, the total cost was reduced by 20.09%. © 2023 by the authors.
ABSTRACT
During natural disasters or accidents, an emergency logistics network aims to ensure the distribution of relief supplies to victims in time and efficiently. When the coronavirus disease 2019 (COVID-19) emerged, the government closed the outbreak areas to control the risk of transmission. The closed areas were divided into high-risk and middle-/low-risk areas, and travel restrictions were enforced in the different risk areas. The distribution of daily essential supplies to residents in the closed areas became a major challenge for the government. This study introduces a new variant of the vehicle routing problem with travel restrictions in closed areas called the two-echelon emergency vehicle routing problem with time window assignment (2E-EVRPTWA). 2E-EVRPTWA involves transporting goods from distribution centers (DCs) to satellites in high-risk areas in the first echelon and delivering goods from DCs or satellites to customers in the second echelon. Vehicle sharing and time window assignment (TWA) strategies are applied to optimize the transportation resource configuration and improve the operational efficiency of the emergency logistics network. A tri-objective mathematical model for 2E-EVRPTWA is also constructed to minimize the total operating cost, total delivery time, and number of vehicles. A multi-objective adaptive large neighborhood search with split algorithm (MOALNS-SA) is proposed to obtain the Pareto optimal solution for 2E-EVRPTWA. The split algorithm (SA) calculates the objective values associated with each solution and assigns multiple trips to shared vehicles. A non-dominated sorting strategy is used to retain the optimal labels obtained with the SA algorithm and evaluate the quality of the multi-objective solution. The TWA strategy embedded in MOALNS-SA assigns appropriate candidate time windows to customers. The proposed MOALNS-SA produces results that are comparable with the CPLEX solver and those of the self-learning non-dominated sorting genetic algorithm-II, multi-objective ant colony algorithm, and multi-objective particle swarm optimization algorithm for 2E-EVRPTWA. A real-world COVID-19 case study from Chongqing City, China, is performed to test the performance of the proposed model and algorithm. This study helps the government and logistics enterprises design an efficient, collaborative, emergency logistics network, and promote the healthy and sustainable development of cities.
ABSTRACT
As a typical representative of the regional economies' integration, the Yangtze River Delta region presents the development trend of emergency logistics integration under the background of the global epidemic of COVID-19, especially the outbreak in Shanghai. A scientific evaluation of the integration level of regional emergency logistics is crucial to the accurate construction of a post-epidemic emergency logistics system in the Yangtze River Delta region. This paper defines regional integration of emergency logistics as two dimensions of high-quality development and equilibrium development, and constructs a regional emergency logistics integration level evaluation index system containing 14 indicators for four factors: emergency logistics infrastructure, resource support, information sharing and mechanisms. A two-stage evaluation model is used to evaluate the integration level of emergency logistics in the Yangtze River Delta region, and the results are compared with the Beijing-Tianjin-Hebei region. According to the results, the integration of emergency logistics in the Yangtze River Delta region is at a medium level, with the highest integration level of emergency logistics infrastructure, the lowest integration level of emergency logistics information sharing, and the medium integration level of emergency logistics resource support and emergency logistics institutional mechanism. The density of integrated transport network and the efficiency of single-vehicle freight completion have the highest and lowest integration levels in the Yangtze River Delta region, respectively. And the integrated development level of emergency logistics in the Yangtze River Delta region is better than that in the Beijing-Tianjin-Hebei region, but there is little difference between the two, mainly due to the high level of integration of emergency logistics infrastructure and emergency logistics resource support. © 2022 IEEE.
ABSTRACT
At the early stage of a major public health emergency outbreak, there exists an imbalance between supply and demand in the distribution of emergency supplies. To improve the efficiency of emergency medical service equipment and relieve the treatment pressure of each medical treatment point, one of the most important factors is the emergency medical equipment logistics distribution. Based on the actual data of medical equipment demand during the epidemic and the characteristics of emergencies, this study proposed an evaluation index system for emergency medical equipment demand point urgency, based on the number of patients, the number of available inpatient beds, and other influencing factors as the index. An urban emergency medical equipment distribution model considering the urgency of demand, the distribution time window, and vehicle load was constructed with the constraints. Wuhan, Hubei Province, China, at the beginning of the outbreak was selected as a validation example, and the Criteria Importance Though Intercriteria Correlation (CRITIC) method and the genetic algorithm were used to simulate and validate the model with and without considering the demand urgency. The results show that under the public health emergencies, the distribution path designed to respond to different levels of urgency demand for medical equipment is the most efficient path and reduces the total distribution cost by 5%.
Subject(s)
Emergency Medical Services , Epidemics , China/epidemiology , Emergencies , Humans , Public HealthABSTRACT
Considering the emergency risks and uncertainties of emergency recycling processes, this research builds a tripartite evolutionary game model of government, logistics enterprises, and environmental non-governmental organizations (NGOs) to study the interaction mechanism. Based on the analysis of evolutionary stable strategy (ESS), this research uses MATLAB R2018b to mainly show the strategy choice trends of logistics enterprises in various scenarios including “Government Failure”, as well as the mutual impacts of government and environmental NGOs’ strategy selection. The research found that (1) the government has an important role in efficiently promoting logistics enterprises’ participation;(2) the net benefits of logistics enterprises and environmental NGOs, as key factors that directly affect the game results, are influenced by emergency risks and uncertainty, respectively;(3) environmental NGOs not only play an effective complementary role to government functions, including in the “Government Failure” context, but can also urge the government to perform regulatory functions. This research enriches the study in the field of the combination of evolutionary game theory and reverse emergency logistics as well as providing a reference for the government in developing economic and administrative policies to optimize the recycling and disposal of emergency relief.
ABSTRACT
Disasters such as earthquakes, typhoons, floods and COVID-19 continue to threaten the lives of people in all countries. In order to cover the basic needs of the victims, emergency logistics should be implemented in time. Location-routing problem (LRP) tackles facility location problem and vehicle routing problem simultaneously to obtain the overall optimization. In response to the shortage of relief materials in the early post-disaster stage, a multi-objective model for the LRP considering fairness is constructed by eval-uating the urgency coefficients of all demand points. The objectives are the lowest cost, delivery time and degree of dissatisfaction. Since LRP is a NP-hard problem, a hybrid metaheuristic algorithm of Discrete Particle Swarm Opti-mization (DPSO) and Harris Hawks Optimization (HHO) is designed to solve the model. In addition, three improvement strategies, namely elite-opposition learning, nonlinear escaping energy, multi-probability random walk, are intro-duced to enhance its execution efficiency. Finally, the effectiveness and perfor-mance of the LRP model and the hybrid metaheuristic algorithm are verified by a case study of COVID-19 in Wuhan. It demonstrates that the hybrid meta-heuristic algorithm is more competitive with higher accuracy and the ability to jump out of the local optimum than other metaheuristic algorithms.
ABSTRACT
The demand for emergency medical facilities (EMFs) has witnessed an explosive growth recently due to the COVID-19 pandemic and the rapid spread of the virus. To expedite the location of EMFs and the allocation of patients to these facilities at times of disaster, a location-allocation problem (LAP) model that can help EMFs cope with major public health emergencies was proposed in this study. Given the influence of the number of COVID-19-infected persons on the demand for EMFs, a grey forecasting model was also utilized to predict the accumulative COVID-19 cases during the pandemic and to calculate the demand for EMFs. A serial-number-coded genetic algorithm (SNCGA) was proposed, and dynamic variation was used to accelerate the convergence. This algorithm was programmed using MATLAB, and the emergency medical facility LAP (EMFLAP) model was solved using the simple (standard) genetic algorithm (SGA) and SNCGA. Results show that the EMFLAP plan based on SNCGA consumes 8.34% less time than that based on SGA, and the calculation time of SNCGA is 20.25% shorter than that of SGA. Therefore, SNCGA is proven convenient for processing the model constraint conditions, for naturally describing the available solutions to a problem, for improving the complexity of algorithms, and for reducing the total time consumed by EMFLAP plans. The proposed method can guide emergency management personnel in designing an EMFLAP decision scheme.
Subject(s)
COVID-19 , Public Health , Algorithms , COVID-19/epidemiology , Emergencies , Humans , PandemicsABSTRACT
The COVID-19 epidemic is spreading globally, and the efficient operation of emergency logistics can effectively reduce the harm caused by the epidemic. Considering the characteristics of COVID-19 and the speed of response required by emergency logistics, this paper takes the COVID-19 epidemic as the background and the circulation of medical supplies as the research object, constructs the operation framework of emergency logistics, designs the operation process of emergency logistics under the COVID-19 epidemic, and makes a detailed analysis of each link. It is expected to provide a reference for improving the emergency management system in China. © 2021 SPIE
ABSTRACT
The coronavirus disease 2019 (COVID-19) epidemic has spread worldwide, posing a great threat to human beings. The stay-home quarantine is an effective way to reduce physical contacts and the associated COVID-19 transmission risk, which requires the support of efficient living materials (such as meats, vegetables, grain, and oil) delivery. Notably, the presence of potential infected individuals increases the COVID-19 transmission risk during the delivery. The deliveryman may be the medium through which the virus spreads among urban residents. However, traditional delivery route optimization methods don't take the virus transmission risk into account. Here, we propose a novel living material delivery route approach considering the possible COVID-19 transmission during the delivery. A complex network-based virus transmission model is developed to simulate the possible COVID-19 infection between urban residents and the deliverymen. A bi-objective model considering the COVID-19 transmission risk and the total route length is proposed and solved by the hybrid meta-heuristics integrating the adaptive large neighborhood search and simulated annealing. The experiment was conducted in Wuhan, China to assess the performance of the proposed approach. The results demonstrate that 935 vehicles will totally travel 56,424.55 km to deliver necessary living materials to 3,154 neighborhoods, with total risk [Formula: see text]. The presented approach reduces the risk of COVID-19 transmission by 67.55% compared to traditional distance-based optimization methods. The presented approach can facilitate a well response to the COVID-19 in the transportation sector.
ABSTRACT
While some reports show that the existing real-life medical resources allocations during epidemic outbreaks are myopic, some experts claim that medical resources allocations based on foresighted future allocations might enable a better balance of supply and demand. To investigate this claim, we develop a foresighted medical resources allocation model to help governments manage large-scale epidemic outbreaks. We formulate a demand forecasting model with a general demand forecasting function based on the last-period demands, extra demand caused by the last-period unfulfilled demand, and uncertain demand. In the foresighted allocation model, the government decides the current-period allocation based on the foresighted demand, which considers the last-period area demand and uncertain demand from the current period to the end of a planning horizon, using a stochastic dynamic program. We find that the optimal allocation is a function of the allocation capacity in each period. The optimal foresighted allocation is always higher than the optimal static (one-period) allocation and decreases with allocation capacity. When the allocation capacity is sufficiently large, the foresighted demand is close to the static demand. Besides, if the cost of oversupply is close to zero, the optimal allocations for both the foresighted allocation and one-period models are the allocation capacity. Our results provide useful managerial implications for a government contemplating medical resources allocation in response to an epidemic outbreak.
ABSTRACT
Global public health emergencies frequently occur, and emergency management is facing huge challenges. As one of the important rescue methods, emergency logistics plays an important role in effectively responding to public health emergencies. The sudden outbreak of COVID-19 in 2019 has severely affected the normal lives of the Chinese people. Cities are extremely susceptible to public health emergencies, especially reflected in the imperfect development of emergency logistics centers. Relevant emergency rescue materials cannot be reasonably allocated and distributed, resulting in low efficiency in the delivery of rescue resources and bringing great impact to people's lives inconvenient. Therefore, this article is based on the maximum coverage model and analytical hierarchy process (AHP) method, taking Wuhan City, Hubei Province as an example, to study the location of emergency logistics centers in the context of public health incidents. © Aussino Academic Publishing House All rights reserved.
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The stockpiling, delivery, and provision of emergency material were in the public gaze of millions of people when the coronavirus disease 2019 (COVID-19) broke out. Civil-military integration emergency logistics silently opened up the "second battlefield" of anti-epidemic, and established a lifeline under that emergency situation. Research on the construction of civil-military integrated logistics system plays an extremely important role and occupies a significant position in ensuring social stability and security as well as the stable development of social economy in China. The modern economy driven by the Internet, Internet of Things, and big data demonstrates a rapid growing trend calling for efficient, fast, and convenient logistics. It is urgent to upgrade or build an intelligent logistics system with intelligent technology and unmanned technology as the core to meet the international and domestic market demand. As mentioned above, this paper analyzes and expounds the construction problem and practical significance of civil-military integration emergency logistics system based on unmanned technology, and puts forward the strategy of constructing civil-military integration emergency logistics system with unmanned technology under the new system. © 2022 Journal of Beijing Institute of Technology
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In this COVID-19 epidemic, due to insufficient awareness of the impact of sudden public health emergencies on agricultural logistics at this stage, agricultural products were left unsold, stocks were backlogged, and losses were severe. In the process of distribution, we should not only ensure a short time cycle and avoid the contamination of agricultural products by foreign bacteria, but also pay attention to the waste of human, material, and financial resources. Therefore, this study mainly adopts the combination of the petrochemical network and block chain to build an agricultural products emergency logistics model. This paper first shows the operation mechanism of the petri dish network and blockchain coupling in the form of a graph and then uses the culture network modelling and simulation tool PIPE to directly verify the construction model. It is proved that the structure and overall business process of the agricultural products logistics system constructed by combining the Petri net and block chain are reasonable, reliable, and feasible in practical application and development. It is hoped that this study can provide a reference direction for agricultural emergency logistics.
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This article focuses on the deficiencies in the construction of emergency logistics and material guarantee systems that have been exposed during the prevention and control of the coronavirus epidemic. Establish an emergency logistics supply system to solve the current slow emergency response and other problems. Heavy. This paper takes the vehicle distribution problem as the background and uses the ant colony algorithm to solve the emergency logistics distribution vehicle scheduling model. On the basis of a time window, the transportation distance and cost of each node of the emergency system are considered to construct a model. According to the characteristics of the model, an ant colony algorithm solution method is designed, and an improved analysis is made for ant path selection. © 2021 IEEE.
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With the progress and development of social science and technology, various information technologies have been deeply integrated into people's lives. The Internet of Things is an emerging industry of information technology, and the logistics industry is the major direction of this technology application. Especially during the COVID-19 outbreak, the Internet of Things technology provides important support for emergency logistics distribution. This thesis is based on the concept of the Internet of Things, discovers and studies the problems and deficiencies of current emergency logistics distribution of our country by comparing the current situation of emergency logistics distribution at home and abroad, and proposes relevant measures to solve these problems, as well as provides effective scientific theoretical support to achieve the purpose of distribution optimization. © 2021 ACM.
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The sudden outbreak of COVID-19 has not only affected people's normal life, but also brought certain impact on logistics. People's demand for agricultural products suddenly increased in a short time, and agricultural products logistics didn't have time to respond. Many new problems have been exposed, because there are many intermediate links in agricultural products logistics, so on the basis of higher logistics cost, it also increases the problem that logistics cannot guarantee timely supply. In addition, the price of agricultural products is low, and the cost of advanced technology is high, so it is impossible to use modern technology to trace the source of agricultural products. During the epidemic period, because the severity of the epidemic varies from place to place, it is particularly important to trace the source of products;at the same time, due to the sudden outbreak of the epidemic, it also brought challenges to emergency logistics, and the response of emergency logistics in various places was slow. However, the epidemic has brought difficulties to logistics and also created opportunities for the development of smart logistics. In order to avoid human contact, information registration systems have been adopted in various places, and unmanned driving, automatic warehousing, automatic distribution and logistics robots have been put into use, which has promoted the sharing of information by smart logistics using the Internet and the intelligentization of logistics operation process. © 2021 IEEE
ABSTRACT
The concept of intelligent development of the logistics industry has been put forward to promote the deep integration of new generation information technology such as big data, block chain, 5G, artificial intelligence and its intelligent facilities and equipment with logistics activities. While in recent years, the outbreak of the COVID-19 has not only attracted worldwide attention, but also posed a challenge to the emergency logistics guarantee system throughout China in the process of epidemic prevention and control. In this paper, based on the existing research, the mechanism of material circulation under emergency is explored and improved based on blockchain with cryptography and smart contract technologies. After innovation and optimization, the mechanism makes it possible to improve the technology of emergency logistics and the level of deep application of wisdom, providing reasonable suggestions and improvement measures for the future management system. © 2021 IEEE.
ABSTRACT
BACKGROUND AND AIM: In the long-term prevention of the COVID-19 pandemic, parameters may change frequently for various reasons, such as the emergence of mutant strains and changes in government policies. These changes will affect the efficiency of the current emergency logistics network. Public health emergencies have typical unstructured characteristics such as blurred transmission boundaries and dynamic time-varying scenarios, thus requiring continuous adjustment of emergency logistics network to adapt to the actual situation and make a better rescue. PRACTICAL SIGNIFICANCE: The infectivity of public health emergencies has shown a tendency that it first increased and then decreased in the initial decision-making cycle, and finally reached the lowest point in a certain decision-making cycle. This suggests that the number of patients will peak at some point in the cycle, after which the public health emergency will then be brought under control and be resolved. Therefore, in the design of emergency logistics network, the infectious ability of public health emergencies should be fully considered (ie, the prediction of the number of susceptible population should be based on the real-time change of the infectious ability of public health emergencies), so as to make the emergency logistics network more reasonable. METHODS: In this paper, we build a data-driven dynamic adjustment and optimization model for the decision-making framework with an innovative emergency logistics network in this paper. The proposed model divides the response time to emergency into several consecutive decision-making cycles, and each of them contains four repetitive steps: (1) analysis of public health emergency transmission; (2) design of emergency logistics network; (3) data collection and processing; (4) adjustment and update of parameters. RESULTS: The result of the experiment shows that dynamic adjustment and update of parameters help to improve the accuracy of describing the evolution of public health emergency transmission. The model successively transforms the public health emergency response into the co-evolution of data learning and optimal allocation of resources. CONCLUSION: Based on the above results, it is concluded that the model we designed in this paper can provide multiple real-time and effective suggestions for policy adjustment in public health emergency management. When responding to other emergencies, our model can offer helpful decision-making references.